scholarly journals Discovery and engineering of low work function perovskite materials

2021 ◽  
Author(s):  
Tianyu Ma ◽  
Ryan Jacobs ◽  
John Booske ◽  
Dane Morgan
Keyword(s):  
Work Function ◽  
High Throughput ◽  
Cathode Materials ◽  
Perovskite Materials ◽  
Dft Simulations

High throughput DFT simulations yield 7 low work function perovskites as promising cathode materials.

Relating voltage and thermal safety in Li-ion battery cathodes: a high-throughput computational study

2015 ◽  
Vol 17 (8) ◽  
pp. 5942-5953 ◽  
Author(s):  
Anubhav Jain ◽  
Geoffroy Hautier ◽  
Shyue Ping Ong ◽  
Stephen Dacek ◽  
Gerbrand Ceder
Keyword(s):  
Dft Calculations ◽  
High Throughput ◽  
High Voltage ◽  
Cathode Materials ◽  
Inverse Relationship ◽  
Computational Study ◽  
Li Ion Battery ◽  
Thermal Safety ◽  
Li Ion

High voltage and high thermal safety are desirable characteristics of cathode materials, but difficult to achieve simultaneously DFT calculations on >1400 Li ion battery cathode materials indicate a complex inverse relationship between voltage and thermal safety.

Influence of cathode material type on the electrical breakdown behaviors of DC discharge

2020 ◽  
Vol 98 (8) ◽  
pp. 726-731
Author(s):  
F. Diab ◽  
W.H. Gaber ◽  
M.E. Abdel-kader ◽  
B.A. Soliman ◽  
M.A. Abd Al-Halim
Keyword(s):  
Cathode Material ◽  
Work Function ◽  
Breakdown Voltage ◽  
Cathode Materials ◽  
Electrical Breakdown ◽  
Ionization Efficiency ◽  
Parallel Plates ◽  
Maximum Value ◽  
Dc Discharge ◽  
Work Functions

Paschen curves were studied using different cathode materials such as magnesium, zinc, and carbon graphite by discharge in argon gas of a pressure range between 0.08 and 3 Torr using a parallel plates configuration. The first and second Townsend coefficients (α and γ, respectively) and the ionization efficiency (η) of different cathode materials were deduced from Paschen curves as a function of the reduced field (E/P). The minimum breakdown voltage was found to be about 242 V for Mg material, which has the lowest work function, while carbon graphite has a higher breakdown voltage of 283 V due to its higher work function. The second coefficient γ was increased as a function of E/P and has higher values for materials of lower work functions, and a similar trend of γ is obtained as a function of the ion mean energy. On the other hand, the first coefficient α has a reverse behavior with both E/P and the work function of the cathode materials compared with the second coefficient. The ionization efficiency of the three cathode materials is identical, as η depends only on the gas properties and not the cathode material. η has a maximum value of about 0.025 V−1 for an E/P of about 185 Vcm−1Torr−1, corresponding to the maximum ionizing ability of electrons. The validation of the breakdown results has been confirmed by conferring with other published experimental measurements.

Exploring Fuel Cell Cathode Materials: A High Throughput Calculation Approach

2019 ◽  
Vol 25 (1) ◽  
pp. 1335-1344 ◽  
Author(s):  
Jacob Gavartin ◽  
Misbah Sarwar ◽  
Dimitrios Papageorgopoulos ◽  
David Gunn ◽  
Sonia Garcia ◽  
...  
Keyword(s):  
Fuel Cell ◽  
High Throughput ◽  
Cathode Materials ◽  
Fuel Cell Cathode ◽  
Cell Cathode

Exploring fuel cell cathode materials using ab initio high throughput calculations and validation using carbon supported Pt alloy catalysts

2020 ◽  
Vol 22 (10) ◽  
pp. 5902-5914 ◽  
Author(s):  
Misbah Sarwar ◽  
Jacob L. Gavartin ◽  
Alex Martinez Bonastre ◽  
Sonia Garcia Lopez ◽  
David Thompsett ◽  
...  
Keyword(s):  
Experimental Study ◽  
Fuel Cell ◽  
High Throughput ◽  
Cathode Materials ◽  
Pem Fuel Cells ◽  
Reduction Reaction ◽  
Pt Alloy Catalysts ◽  
Fuel Cell Cathode ◽  
Pt Alloy ◽  
Alloy Catalysts

A combined DFT and experimental study of Pt3M alloys activity and stability for oxygen reduction reaction in PEM fuel cells.

SoftBV – a software tool for screening the materials genome of inorganic fast ion conductors

2019 ◽  
Vol 75 (1) ◽  
pp. 18-33 ◽  
Author(s):  
Haomin Chen ◽  
Lee Loong Wong ◽  
Stefan Adams
Keyword(s):  
Force Field ◽  
High Throughput ◽  
High Throughput Screening ◽  
Density Functional ◽  
Inorganic Compounds ◽  
Computational Cost ◽  
Lewis Base ◽  
Computational Screening ◽  
Wide Range ◽  
Dft Simulations

The identification of materials for advanced energy-storage systems is still mostly based on experimental trial and error. Increasingly, computational tools are sought to accelerate materials discovery by computational predictions. Here are introduced a set of computationally inexpensive software tools that exploit the bond-valence-based empirical force field previously developed by the authors to enable high-throughput computational screening of experimental or simulated crystal-structure models of battery materials predicting a variety of properties of technological relevance, including a structure plausibility check, surface energies, an inventory of equilibrium and interstitial sites, the topology of ion-migration paths in between those sites, the respective migration barriers and the site-specific attempt frequencies. All of these can be predicted from CIF files of structure models at a minute fraction of the computational cost of density functional theory (DFT) simulations, and with the added advantage that all the relevant pathway segments are analysed instead of arbitrarily predetermined paths. The capabilities and limitations of the approach are evaluated for a wide range of ion-conducting solids. An integrated simple kinetic Monte Carlo simulation provides rough (but less reliable) predictions of the absolute conductivity at a given temperature. The automated adaptation of the force field to the composition and charge distribution in the simulated material allows for a high transferability of the force field within a wide range of Lewis acid–Lewis base-type ionic inorganic compounds as necessary for high-throughput screening. While the transferability and precision will not reach the same levels as in DFT simulations, the fact that the computational cost is several orders of magnitude lower allows the application of the approach not only to pre-screen databases of simple structure prototypes but also to structure models of complex disordered or amorphous phases, and provides a path to expand the analysis to charge transfer across interfaces that would be difficult to cover by ab initio methods.

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